chore: litellm oss staging 250626 - #31305
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… validate_environment
…) when no message_delta arrives The Anthropic streaming protocol emits `message_start.usage.output_tokens=1` as a placeholder cursor; the real cumulative output count only arrives in the final `message_delta` event. When a stream is cancelled before `message_delta` lands (common for thinking models on long-tail prompts), ChunkProcessor._calculate_usage_per_chunk's last-wins accumulator left completion_tokens stuck at 1. Because 1 is truthy, the `completion_tokens or token_counter(text=...)` fallback in calculate_usage() never fired, and requests were billed for 1 output token even when several thousand tokens of text had actually streamed. Fix: track whether any chunk's completion_tokens exceeded 1 (saw_non_cursor_completion). If the only update we saw was the cursor, reset completion_tokens to 0 so the text-based fallback estimates from the real completion content. Legitimate 1-token completions (model returns "Yes." etc.) are unaffected in practice — token_counter on a 1-token completion_output also yields ~1, so billing stays approximately correct. Tests: - TestAnthropicCursorBug (6 cases) — pins the post-fix behavior - TestNonAnthropicStreamingIntact (2 cases) — guards against regression on providers without the cursor pattern All 8 new tests pass; 9 existing streaming_chunk_builder_utils tests still pass.
…message_delta arrival Addresses both Greptile P2 threads on PR #30420: CLASS A — Anthropic-specific heuristic was applied globally ============================================================ The `completion_tokens == 1 and not saw_non_cursor_completion` reset lived in provider-neutral `streaming_chunk_builder_utils.py`. Any non-Anthropic provider that legitimately reports completion_tokens=1 in a single usage chunk (perfectly normal for short OpenAI / Bedrock / Vertex single-token replies with stream_options.include_usage=true) would have its value silently rewritten to 0 and re-billed via token_counter — producing a different number than what the provider actually charged. Fix: gate the reset on `custom_llm_provider == "anthropic"`, resolved from the first chunk's `_hidden_params` (the same field set by streaming_handler.py:722 on the live path). Unknown / missing provider is treated as non-Anthropic and skips the reset, so newer providers and custom plugins are also safe by default. CLASS B — `saw_non_cursor_completion` missed legitimate single-token replies ============================================================ Previous condition was `usage_chunk_dict["completion_tokens"] > 1`, which never fires for an Anthropic stream where the model legitimately emits exactly one output token (e.g., "Yes."). Anthropic still sends message_start (output_tokens=1, the cursor) AND message_delta (output_tokens=1, the real value) — same value, but two distinct usage events. The old check couldn't tell that apart from a cancelled stream where only message_start landed. Fix: track `completion_usage_updates` and flip `saw_non_cursor_completion` when EITHER (1) the value exceeds 1 (definitely not a placeholder), OR (2) we've seen >=2 completion-bearing usage events (positive evidence that message_delta arrived). Cancelled cursor-only streams still have exactly one event and still hit the reset; cache chunks with completion_tokens=0 don't count toward the threshold. Tests ============================================================ - _make_chunk now sets `_hidden_params["custom_llm_provider"]` (default "anthropic") so the gate is exercised by every existing test — none of them needed assertion changes besides the legitimate-single- token case, which now expects exactly 1 (was a fuzzy 0..3 range). - New: test_anthropic_cache_only_chunks_after_message_start_still_resets - New: test_non_anthropic_provider_completion_tokens_one_not_reset - New: test_unknown_provider_completion_tokens_one_not_reset 11/11 tests pass.
Co-authored-by: songkuan-zheng <songkuan-zheng@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
When Gemini API returns toolCall and toolResponse parts, they might have different thoughtSignatures. Previously, LiteLLM merged them into a single dict, overwriting the response's thoughtSignature with the call's. This fix extracts them separately and re-injects them correctly. TAG=agy CONV=755b21d0-3200-40bc-bd1a-bb58a378a9a6
- Fix orphan-response thoughtSignature regression by copying thought_signature to response_thought_signature - Add missing assertions in existing tests - Add new unit tests for orphan-response signature handling TAG=agy CONV=755b21d0-3200-40bc-bd1a-bb58a378a9a6
- Add alias and server_id fields to mcp_info object in /mcp-rest/tools/list endpoint - Update rest_endpoints.py to surface alias from server config - Add test coverage in test_mcp_server.py and test_rest_endpoints.py Fixes #31015
A NaN/-inf spend would bypass spend >= max_budget enforcement. Add a shared finite-value guard, defined above the litellm.proxy.* imports to avoid the module-level cyclic-import warning.
Gate the admin check on the presence of `spend` (not a value diff): the DB spend lags the live cross-pod counter, so an "unchanged" spend on the non-admin path let a key owner / team member overwrite the live counter below real usage. Also reject NaN/+-inf spend before the DB write.
A direct spend change on /user/update wrote the DB row but left the warm
cross-pod counter at the stale value, so enforcement kept reading the old
spend. Invalidate spend:user:{user_id} after the write (reseed-from-DB),
and reject non-finite spend before the write.
…outer (#28244) The semantic cache's embedding model is a proxy Router alias whose AWS credentials (aws_role_name, aws_session_name) live only in the Router deployment's litellm_params. The sync embedding paths called litellm.embedding() directly, bypassing the Router, so they could neither resolve the alias nor assume the configured role; cross-account Bedrock semantic caching failed with "bedrock:InvokeModel is not authorized". On Redis this surfaced at proxy startup because redisvl's CustomTextVectorizer eagerly fires a dimension-probe embedding during cache construction, while llm_router is still None. Fix A: make the sync paths mirror the already-correct async paths. A shared, dependency-injected helper (litellm/caching/_embedding_router.py) decides whether to route through llm_router.embedding(...) when the model is a Router deployment, else fall back to direct litellm.embedding(...). Redis and qdrant sync set_cache/get_cache now precompute the embedding and pass vector= to the backend, exactly as the async astore/acheck already do. Both async _get_async_embedding methods are unified onto the same helper and now forward the caller's full metadata instead of a hand-picked subset. Fix B (Redis only): defer redisvl index construction from __init__ into a lazy, memoized llmcache property, so the dimension-probe embedding fires on first cache use, after llm_router is wired. A failed build is not memoized, so a transient outage recovers on the next request. Known limitation: resolve_embedding_router gates on an exact model-name match (same as the shipped async path); wildcard/alias/team-public routes still fall back to direct embedding. Tracked as a follow-up.
Address review feedback on the semantic-cache aws-role fix (#28244): - resolve_embedding_router now skips deployment entries missing model_name instead of raising KeyError on a malformed model_list (Greptile P2); add a regression test that fails on the old direct-key access. - Replace the `**kwargs: Any` passthrough on the four cache _get_embedding / _get_async_embedding helpers with an explicit, typed `metadata: Optional[Dict[str, Any]] = None` parameter. The helpers only ever consumed kwargs["metadata"], so this is behavior-preserving, makes the forwarded field obvious at the call site, and removes three bare-Any annotations (keeps the strict-rule ANN401 budget within ceiling). - Note in _build_llmcache that redisvl's dimension-probe embedding adds one extra billable embedding on the first cache request (Greptile P2).
Dashboard Test Connection for bedrock_mantle/openai.gpt-5.4 and openai.gpt-5.5 was failing with maximum recursion depth errors and "model does not exist" Route detection in the bedrock provider matched route tokens by plain substring, so the bedrock_mantle/ prefix was mistaken for the mantle/ invoke route and the body model was rewritten to bedrock_openai.gpt-5.5; route tokens now only match at a path-segment boundary so the bare model name is preserved A responses-mode model whose provider has no responses config bounced forever between the responses API and chat completions; the responses to completion fallback now tags its call so completion() does not bridge back, breaking the loop The Test Connection endpoint hardcoded the test mode to chat, which disabled mode auto-detection for responses-only models; the default is now None so the mode is detected from model capabilities acompletion() now drops a duplicate acompletion kwarg before building the partial and treats model_info=None as an empty dict to avoid a NoneType crash
…gumentType regression Adds the regression coverage codecov flagged on the two responses to completion bridge guard lines and the bedrock route-prefix helper. The handler tests drive both the sync and async fallback paths with litellm.completion and litellm.acompletion mocked, and assert the forwarded kwargs carry _skip_responses_api_bridge=True, so dropping either flag line fails the suite. The common_utils tests assert that bedrock_mantle/openai.gpt-5.x no longer resolves to the mantle route while the genuine mantle/ and bedrock/mantle/ ids still do, exercising both branches of _model_has_route_prefix. Also aligns update_messages_with_model_file_ids model_id to Optional[str], matching its Responses API sibling, so the defensive model_info fallback no longer introduces a new reportArgumentType in completion(); the file-id lookup narrows model_id before the dict get
…mode The test_model_connection mode body param default changed from chat to None so the mode is auto-detected from model capabilities, which makes the field optional in the proxy OpenAPI spec. Regenerate the committed schema so the dashboard types match: mode becomes optional and the description and default JSDoc follow the spec, keeping the Check UI API Types Sync gate green
…boundary Migrates the remaining substring route checks to the existing _model_has_route_prefix helper so every explicit route token matches only as a leading path segment, consistent with get_bedrock_route and the mantle route. Covers _explicit_converse_route, _explicit_claude_platform_route, _explicit_invoke_route, _explicit_agent_route, _explicit_agentcore_route, _explicit_converse_like_route, _explicit_async_invoke_route and _explicit_openai_route. This also stops invoke/ from substring-matching async_invoke/. Route precedence and order are unchanged, and a note on the segment invariant is added to the helper docstring
Exercises all eight migrated _explicit_*_route helpers (converse, converse_like, invoke, async_invoke, agent, agentcore, claude_platform, openai) directly: each matches its token as a leading path segment and rejects the token glued to a preceding segment, so reverting any method to the old substring check fails the suite. Also asserts invoke/ no longer matches async_invoke/ models, the concrete improvement of the segment-boundary migration
Negative spend is intentionally permitted so admins can grant extra allowance for the current budget period only, without raising the recurring budget ceiling. Cover it explicitly in validate_finite_spend and via the /user/update invalidation test.
Google's native generateContent REST body carries safetySettings, toolConfig, cachedContent and labels at the top level as siblings of generationConfig. The proxy's :generateContent endpoint spread them into agenerate_content as loose kwargs and then dropped them, so callers had to wrap them in extra_body for them to take effect; safetySettings, for instance, was silently ignored The provider config now exposes the native top-level field names and setup_generate_content_call collects whichever are present, merging them into the outgoing request body through the existing extra_body merge so they reach Google verbatim. An explicit extra_body still wins on conflict. The sync generate_content_stream path now also forwards systemInstruction, matching the other three entry points Fixes #12671 Claude-Session: https://claude.ai/code/session_016MFtMXokCjT8u6mvyASudK
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- Replace Optional[X] with X | None (UP045) in 8 files - Replace Any return/param types with concrete types or object (ANN401) - Extract _make_api_key_auth_header helper to reduce get_anthropic_headers complexity below C901 threshold (17 → 14) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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…r via prefix Users who pass a key already prefixed with "Bearer " get Authorization: Bearer. All other keys continue to use x-api-key, preserving backward compatibility with custom api_base endpoints that expect x-api-key rather than Authorization. Also consolidates get_auth_header to reuse _make_api_key_auth_header helper, eliminating the duplicated custom-endpoint routing logic. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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…tom api_base The backwards-compat change broke existing tests that verify the intentional Bearer-for-custom-base behavior (Fixes #30926). Restore original logic while keeping the _make_api_key_auth_header helper for code deduplication. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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…tom_base flag Previously the auth-header switch from x-api-key to Authorization: Bearer applied unconditionally for non-sk-ant- keys on a custom api_base, silently breaking existing deployments that proxied to gateways expecting x-api-key. Introduce use_bearer_for_custom_base: bool = False on _make_api_key_auth_header, get_anthropic_headers, and get_auth_header. validate_environment reads it from litellm_params so callers can opt in per-model without any API surface change. Tests updated to pass use_bearer_for_custom_base=True where Bearer behavior is asserted. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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…ache (#29981) DEL was the only Redis cache operation that skipped check_and_fix_namespace, so it targeted the raw SHA256 hash (e.g. 3997c4...) rather than the namespaced key (litellm:3997c4...). This caused two problems: a Redis NOPERM error on deployments with an ACL restricting DEL to the litellm:* pattern, and a silent no-op on all other deployments since the un-prefixed key was never stored.
…on py312) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Cursor Bugbot has reviewed your changes using high effort and found 2 potential issues.
Autofix Details
Bugbot Autofix prepared fixes for both issues found in the latest run.
- ✅ Fixed: Sync cache strips router metadata
- Sync cache lookups now pass a copy of request metadata through to semantic cache backends while still copying semantic similarity back to the original metadata.
- ✅ Fixed: Spend invalidation errors swallowed
- Key spend updates now write the spend counter directly and log Redis update failures instead of silently ignoring invalidation errors.
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…ruff gate Extract Anthropic message_start cursor reset into _reset_anthropic_cursor_completion_tokens and the cross-pod spend-counter invalidation into _invalidate_user_spend_counter_if_changed, keeping both _calculate_usage_per_chunk and _update_single_user_helper under the max-complexity ceiling. Use builtin generics in the new signatures so no new UP006 violations are introduced. Behavior unchanged.
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Type
🆕 New Feature
🐛 Bug Fix
🧹 Refactoring
📖 Documentation
🚄 Infrastructure
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Note
Medium Risk
Touches semantic-cache embedding auth, proxy spend counters and budget validation, and Anthropic streaming usage billing—areas where regressions affect cost or access control, though changes are largely targeted fixes with extensive tests.
Overview
This PR bundles several proxy and core routing fixes with new regression tests.
Semantic caches now share
_embedding_routerso Redis and Qdrant embeddings go through the proxy Router when the embedding model is a deployment (Bedrock role auth, etc.), forwarding full request metadata viabuild_router_embedding_metadata. Redis defers redisvl index build until first use; sync/async paths pass precomputed vectors intostore/check. Cache lookups copy caller metadata into backend kwargs instead of an empty dict.Proxy budget enforcement rejects NaN/±inf spend on user/key updates, tightens key spend admin rules, sets spend counters explicitly after key spend updates (with Redis warning on failure), and invalidates user spend counters after admin spend changes.
Anthropic: optional Bearer auth for custom
api_base; centralized OpenAI→Anthropic usage translation (cache read/create from multiple field shapes); streaming message_startoutput_tokens=1cursor reset (Anthropic-only) so cancelled streams bill from text fallback.Bedrock route detection uses path-segment prefix matching so
bedrock_mantle/is not mistaken formantle/. Google GenAI merges native top-level REST fields (safetySettings,toolConfig, etc.) intoextra_body. Vertex Gemini keeps separate response thought signatures on tool responses. completion() adds_skip_responses_api_bridgeto stop Responses↔completion infinite recursion.Smaller changes: Redis delete applies namespace; MCP REST tools list adds server_id and alias in
mcp_info; team-scoped DB models skip resolvingos.environ/credential refs; health check mode body defaults to auto-detect.Reviewed by Cursor Bugbot for commit 62a7d45. Bugbot is set up for automated code reviews on this repo. Configure here.